Here’s what we said to 200 Geospatial Experts at the United Nations

Last week, over 200 geospatial experts from 150 member states convened at the United Nations to discuss how spatial data and technology are shaping the future of sustainable development in line with the United Nation’s 2030 Sustainable Development Goals (SDGs).

We offered the following advice to our peers in the field: If each of the 193 member states hopes to hit their SDGs by 2030, they must use new data, undertake new analyses, and reach new audiences.

We need to find new data.

To tackle seemingly undefinable SDGs, we need to be identifying new data streams and making sure the partnerships and structures are in place to allow us to make use of that data.

The BBVA Data & Analytics team wanted to know “What is the resilience of a community to a natural disaster?”

BBVA Data & Analytics, in partnership with UN Global Pulse, used fingerprint bank card activity from Baja California Sur, Mexico to assess the difference in how natural disasters affect men and women, in line with the SDG on gender equality. By establishing an average for card payments and cash withdrawals in the area, they discovered that women not only spent twice as much as men preparing for a 2014 hurricane, but that it also took them 30% longer to recover after the fact.

In the words of the data scientists, “This project confirms that financial data can provide timely and precise information to better support vulnerable populations before, during, and after natural disasters.”

We need to use new analyses.

The wealth of data available also demands creative and sophisticated spatial analyses tied to clear problems that needs to be solved.

We shared with the UN a map of vaccination facilities in Kenya that we built for UNICEF. We mapped the population density of one- and two-year-olds in Kenya alongside the number and location of existing vaccination facilities. Using spatial analyses, we could show the best location for UNICEF to build 16 new medical centers planned for the next few years. However, the optimal locations depended on what they wanted to solve for.

If the problem we’re trying to solve is How do we reach the greatest number of Kenyan infants? then we should build nine of those centers in Nairobi, the country’s largest and most densely populated city. But, if the problem we’re trying to solve is How do we reach populations without any access to medical care? then it makes sense to distribute the vaccination centers throughout Kenya’s rural areas.

Conflicting priorities such as these reflect the complexity of implementing the SDGs and the need for intentional analyses.

We need to give new audiences access to new data streams and analysis methods.

With data becoming ever more cumbersome, governments must also enlist private partners and nonprofits to help with these new analyses.

According to geospatial experts, “The Earth and its systems are complex and interconnected, and gaining a comprehensive understanding of these systems and how we interact with them is of critical national and international interest.” To do so, however, requires enormous technological prowess.

Sixty-nine satellites currently monitor the entire globe’s geology, water conditions, sea surface temperatures, and magnetic fields, resulting in a dataset that’s too large for a single government to fully take advantage of. For that reason, Australia recently released the Data Cube, a 200-terabyte set of regular, non-overlapping tiles of gridded sensor data. Because the Cube is analysis ready, interested parties can easily ingest and analyze the satellite images, fully optimizing existing resources in service of the SDGs.

The SDGs are ambitious in their timeline and scope, but we at CARTO believe that by empowering actors with new data, new analyses, and making these available to new audiences, these 17 goals are achievable. As case studies in Mexico, Kenya, and Australia demonstrate, creatively collecting, visualizing, analyzing, and sharing data can provide solutions that were previously unimaginable.